Exploring the Role of AI in Endometriosis Patient Education: Assessing Information Quality and Accuracy

Abstract

The global disease affects many millions of women with endometriosis so misinterpretation and delayed medical assessment are common occurrences. An investigation analyses how artificial intelligence platforms benefit patient education about endometriosis through their contribution to accurate knowledge delivery to patients.

Methods: Research examined existing AI applications in patient education platforms especially for endometriosis treatment. Research analyses studies that appeared from January 2015 to August 2024. The research utilized the databases of PubMed together with IEEE Xplore and Google Scholar to find peer-reviewed articles.

Results: Natural language processing (NLP) and machine learning algorithms powered AI applications show effectiveness in delivering appropriate educational information tailored to patients suffering from endometriosis. The platforms have achieved several key objectives that include clearing up false beliefs and improving patient involvement while granting patients stronger control over their condition-related knowledge.

Conclusion: Multiple data quality problems along with unclear algorithms and privacy issues still hinder the improvement of AI-based endometriosis patient education systems. AI-empowered healthcare training systems bring valuable improvements to patient education that enhances their disease management self-competence implementations in Assisted Reproductive Technology.